There is an increasing demand for methods and systems capable of detection, quantitative characterization, and notification of the presence of chemical, biological, radiological, nuclear, and/or explosive (“CBRNE”) hazards across a broad range of disciplines, including defense, food safety, homeland security, and medical diagnostics, among many others. While there is existing technology for the detection and quantitative identification of chemical and biological hazards, these sensors are generally large, bulky, and/or slow sensor systems that require considerable time and effort to utilize or to move from one location to another. Accordingly, there is a continued need for fast, efficient, and portable sensor systems for hazard detection, as well as for systems that subsequently notify a user of any hazard that is detected.
A chemical attack can include threat chemicals released as an aerosol dispersion. In such an attack, the aerosol dispersion could be composed of threat chemicals in the form of any combination of solid particles, liquid droplets, or vapors. Many CBRNE chemical detectors do not easily collect, concentrate, and analyze chemical threats in all states of matter.
One method used for the identification of biological or chemical threats is Raman spectroscopy. Raman is a form of vibrational spectroscopy proven to exhibit excellent selectivity for the purpose of material identification and has been the handheld liquid/solid analyzer of choice for defense and homeland security applications. Raman spectroscopy utilizes a monochromatic laser to interrogate unknown samples. Depending on the specific wavelength of light, the composition of the background material, and properties of the chemical being interrogated, the light can result in absorption, transmission, reflection, or scattering. Light that is scattered from the sample can result in either elastic collisions resulting in Raleigh scattering or inelastic collisions resulting in Raman scattering. Raman light scattering is the result of a photon exciting the molecule through vibration and rotation of its bonds from a ground state to a virtual energy state. Once the molecule relaxes, it emits a photon and returns to a rotational or vibrational state different from the original ground state. The energy delta between these levels results in a shift of the emitted photon's frequency away from the excitation wavelength. The result is a detection method based on the peak intensities at characteristic shifts measured in wavenumber (cm-1) or wavelength (nm) and attributed to specific molecules, thus generating a Raman spectral “fingerprint” by recording the intensity of light as a function of the energy difference between the laser and Raman scattered light. This output is reproducible and allows development of identification algorithms for the spectral fingerprints. However, Raman detectors are not equipped or configured to collect, detect, or analyze a released aerosol.
One difficulty with fielded Raman detectors is that some background surfaces undergo a competing phenomenon, referred to as fluorescence, which can mask the signal of the analyte. For example, plastics and surfaces with organic binders, paints, and adhesives can obscure a Raman signal and affect the sensitivity of analysis. Modulation of the wavelength of the incident light can alleviate some fluorescence effects, but most fielded instruments operate at a static incident laser wavelength chosen to balance these effects as well as to conserve power, weight, and complexity of the device. Since reducing fluorescence of the sample is not possible at a static wavelength, our invention drastically reduces the interfering background fluorescence and amplifies the analyte signal by providing an ideal collection substrate for and analysis by spectroscopy.
Detection level of this invention as it pertains to a dry chemical aerosols such as acetaminophen have resulted in positive detection and identifications of aerosol clouds down to concentrations of 0.001-0.005 mg/m3 when collected and concentrated over 5 minutes using the device described herein. Detection of chemical aerosol clouds at a concentration of 0.0005 mg/m3 have been achieved following 10 minute collections. Detection levels of liquid droplets of 0.1 μL (100 nanoliters) has been shown to be rapid with the system described herein.
Accordingly, there is a continued need for methods and systems that use Raman spectroscopy to analyze an aerosol.